The accuracy of satellite navigation systems (i.e., Global Navigation Satellite Systems (GNSSs)) rely on legitimate satellite signals. For example, a legitimate satellite signal can be a signal transmitted by a satellite and received by a receiver to communicate time and location information unique to the transmitting satellite. However, various types of illegitimate satellite signals can adversely affect the accuracy of satellite location systems. For example, in urban areas, buildings may get in the way of a direct signal path, causing a faulted signal. Similarly, in mountainous regions, the topography can interfere with a signal's path. Spoofed signals can send false information to a signal receiver. For example, someone may generate spoofed signals that communicate false satellite transmission times or false satellite velocities. If the receiver has no way of rejecting these spoofed signals, it may accept the faulted and/or spoofed signals, causing inaccuracies in the satellite navigation systems.
The consequences of spoofed signals in particular can be detrimental. For example, a spoofer (i.e., a person generating spoofed signals) can cause any vehicle (e.g,. airplane, unmanned aerial vehicle, automobile) using a satellite navigation system to navigate off-path and/or crash. Spoofers can cause such navigation problems in both civilian applications as well as in military applications—anywhere a vehicle is using a satellite navigation system.
Current technologies that can help protect satellite navigation systems against illegitimate signals include RAIM (Receiver Autonomous Integrity Monitoring) and ARAIM (Advanced Receiver Autonomous Integrity Monitoring). These systems are able to detect and exclude fault signals, but are limited in their ability to detect and exclude high numbers of fault or spoofed signals. Further, these systems were developed to detect fault signals from a small number of satellites at any given time.
Random Identify Exemplary (RANSAC) can identify fault or spoofed signals by performing an exhaustive identifying on the data. However, RANSAC is only capable of identifying outlier parameters (i.e., illegitimate signals), and is not capable of identifying legitimate signals. Further, the RANSAC algorithm can compute an inlier and an outlier set for every subset of parameters of a plurality of parameters corresponding to a plurality of satellite signals. The parameters associated with the smallest subset of consistent outliers correspond to the most correct satellite signals.
Other signal-identifying algorithms and technologies can analyze pseudo-range or pseudo-range-rate data, but not both types of data.